Currently, a large number of images are available via various databases located at distributed network locations. With the availability of such a large number of images, techniques for efficiently and accurately retrieving and ranking relevant images in response to a submitted query have gained importance.
Conventionally, image retrieval and ranking models are based solely on textual information associated with images. To this end, the visual content of the image is neglected when identifying and ranking images. Consequently, imperfect search results frequently appear due to mistaken associations between the textual information of an image and the actual image content.